Experimental investigation into the temperature and heat transfer distribution around air-cooled cylinders

This paper describes an experimental investigation into the surface heat transfer coefficient of finned metal cylinders in a free air stream. Ten cylinders were tested with four different fin pitches and five different fin lengths. The cylinders and their fins were designed to be representative of those found on a motorcycle engine with an external cylinder diameter of 100 mm and fin lengths of 10 to 50 mm. The fins of each cylinder were gravity die cast in aluminum allow. Each cylinder was electrically heated and mounted in a wind tunnel which subjected it to a range of air speeds between 2 and 20 m/s. The surface heat transfer coefficient, h, was found primarily to be a function of the air speed and the fin separation, with fin length having a lesser effect. In addition to the determination of an overall heat transfer coefficient, the distribution of cooling around the circumference of each cylinder was also studied. Not surprisingly, the cooling was found to be greatest on the front of the cylinder, which was the side first impinged by the air stream. The cooling of the rear of the cylinder was better than might have been expected and this is quantified.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.

Human information retrieval

Information retrieval in the age of Internet search engines has become part of ordinary discourse and everyday practice: "Google" is a verb in common usage. Thus far, more attention has been given to practical understanding of information retrieval than to a full theoretical account. In Human Information Retrieval, Julian Warner offers a comprehensive overview of information retrieval, synthesizing theories from different disciplines (information and computer science, librarianship and indexing, and information society discourse) and incorporating such disparate systems as WorldCat and Google into a single, robust theoretical framework. There is a need for such a theoretical treatment, he argues, one that reveals the structure and underlying patterns of this complex field while remaining congruent with everyday practice. Warner presents a labor theoretic approach to information retrieval, building on his previously formulated distinction between semantic and syntactic mental labor, arguing that the description and search labor of information retrieval can be understood as both semantic and syntactic in character. Warner's information science approach is rooted in the humanities and the social sciences but informed by an understanding of information technology and information theory. The chapters offer a progressive exposition of the topic, with illustrative examples to explain the concepts presented. Neither narrowly practical nor largely speculative, Human Information Retrieval meets the contemporary need for a broader treatment of information and information systems.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Steady-State and Transient Performance of Biodiesel-Fueled Compression-Ignition-Based Electrical Generation

This paper investigates the performance characteristics of rapeseed methyl ester, EN 14214 biodiesel, when used for electrical generation in compression ignition engines. The work was inspired by the need to replace fossil diesel fuel with a sustainable low carbon alternative while maintaining generator performance, power quality, and compliance with ISO 8528-5. A 50-kVA Perkins diesel engine generator was used to assess the impact of biodiesel with particular regard to gen-set fuel consumption, load acceptance, and associated standards. Tests were performed on the diesel gen-set for islanded and grid-connected modes of operation, hence both steady-state and transient performance were fully explored. Performance comparisons were made with conventional fossil diesel fuel, revealing minimal technical barriers for electrical generation from this sustainable, carbon benign fuel. Recommendations for improved transient performance are proposed and validated through tests.

Project Omnivore: A Variable Compression Ratio ATAC 2-Stroke Engine for Ultra-Wide-Range HCCI Operation on a Variety of Fuels

The paper describes the principal features of Omnivore, a spark-ignition-based research engine designed to investigate the possibility of true wide-range HCCI operation on a variety of fossil and renewable liquid fuels. The engine project is part-funded jointly by the United Kingdom's Department for the Environment, Food and Rural Affairs (DEFRA) and the Department of the Environment of Northern Ireland (DoENI). The engineering team includes Lotus Engineering, Jaguar Cars, Orbital Corporation and Queen's University Belfast.

One Dimensional Modeling of a Turbogenerating Spark Ignition Engine Operating on Biogas

Turbocompounding is generally regarded as the process of recovering a proportion of the exhaust gas energy from a reciprocating engine and applying it to the output power of the crankshaft. In conventional turbocompounding, the power turbine has been mechanically connected to the crankshaft but now a new method has emerged. Recent advances in high speed electrical machines have enabled the power turbine to be coupled to an electric generator. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimize the turbine efficiency for different engine operating conditions.

Comparison of Experimental PIV Data and CFD Simulations for Flow in a Diesel Particulate Filter Inlet Diffuser

Flow maldistribution of the exhaust gas entering a Diesel Particulate Filter (DPF) can cause uneven soot distribution during loading and excessive temperature gradients during the regeneration phase. Minimising the magnitude of this maldistribution is therefore an important consideration in the design of the inlet pipe and diffuser, particularly in situations where packaging constraints dictate bends in the inlet pipe close to the filter, or a sharp diffuser angle. This paper describes the use of Particle Image Velocimetry (PIV) to validate a Computational Fluid Dynamic (CFD) model of the flow within the inlet diffuser of a DPF so that CFD can be used with confidence as a tool to minimise this flow maldistribution. PIV is used to study the flow of gas into a DPF over a range of steady state flow conditions. The distribution of flow approaching the front face of the substrate was of particular interest to this study. Optically clear diffusing cones were designed and placed between pipe and substrate to allow PIV analysis to take place. Stereoscopic PIV was used to eliminate any error produced by the optical aberrations caused by looking through the curved wall of the inlet cone. In parallel to the experiments, numerical analysis was carried out using a CFD program with an incorporated DPF model. Boundary conditions for the CFD simulations were taken from the experimental data, allowing an experimental validation of the numerical results. The CFD model incorporated a DPF model, the cement layers seen in segmented filters and the intumescent matting that is commonly used to pack the filter into a metal casing. The mesh contained approximately 580,000 cells and used the realizable ?-e turbulence model. The CFD simulation predicted both pressure drop across the DPF and the velocity field within the cone and at the DPF face with reasonable accuracy, providing confidence in the use the CFD in future work to design new, more efficient cones.